基于局域世界的无线传感器网络分簇演化模型

符修文; 李文锋

doi:10.11959/j.issn.1000-436x.2015157

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基于局域世界的无线传感器网络分簇演化模型

学术论文 | 更新时间：2024-06-05

- 基于局域世界的无线传感器网络分簇演化模型
- Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory
- 通信学报 2015年36卷第9期页码：204-214
- 作者机构：
  
  武汉理工大学物流工程学院，湖北武汉 430063
- 作者简介：
  
  [ "符修文（1987-），男，河南洛阳人，武汉理工大学博士生，主要研究方向为无线传感器网络抗毁性技术、机会网络。" ]
  [ "李文锋（1966-），男，湖南岳阳人，博士，武汉理工大学教授、博士生导师，主要研究方向为物联网、无线传感器网络、机器人技术。" ]
- 基金信息：
  
  国家“十二五”科技支撑计划基金资助项目(2012BAJ05B07);国家自然科学基金资助项目(61305110);中央高校基本科研业务费专项基金资助项目(135118003)
- DOI：10.11959/j.issn.1000-436x.2015157
  中图分类号： TP393
- 网络出版日期：2015-09，
  
  纸质出版日期：2015-09-25
- 稿件说明：
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符修文, 李文锋. 基于局域世界的无线传感器网络分簇演化模型[J]. 通信学报, 2015,36(9):204-214.

Xiu-wen FU, Wen-feng LI. Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory[J]. Journal on communications, 2015, 36(9): 204-214.
符修文, 李文锋. 基于局域世界的无线传感器网络分簇演化模型[J]. 通信学报, 2015,36(9):204-214. DOI： 10.11959/j.issn.1000-436x.2015157.

Xiu-wen FU, Wen-feng LI. Evolutionary model of heterogeneous clustering wireless sensor networks based on local world theory[J]. Journal on communications, 2015, 36(9): 204-214. DOI： 10.11959/j.issn.1000-436x.2015157.

摘要

当前无线传感器网络无标度演化模型研究往往将网络视为同质网络，且未充分考虑网络在真实情形下的演化特征，导致所获网络拓扑与实际网络差异明显。因此，基于局域世界理论，考虑无线传感器网络典型分簇结构、能耗敏感与真实网络中普遍存在的节点与链路退出的动态性行为等特征，提出无线传感器网络分簇演化模型。该模型与同类研究成果相比，更为接近真实网络情形。利用平均场理论推导出此模型具有无标度特征。通过研究拓扑生长对网络容错性能影响，发现扩大局域世界规模与提升饱和度约束上限可有效提升网络容错性能。与之相反，簇头比例与节点删除概率的上升将导致网络容错性能的下降。

Abstract

Current research on the scale-free evolutionary model of wireless sensor networks (WSN) treated each network as a homogenous one and does not take into account the evolutionary characteristics of the network in realistic scenarios

thus leading to significant differences between homogenous networks and realistic ones.Therefore

based on local-world theory

a heterogonous evolution model of WSN in relation to cluster-structure

energy-sensitivity and dynamic behavior of WSN (e.g.

failures of nodes and links) was proposed.Compared with previous research results

the proposed model is closer to reality.By using the mean-field theory

the scale-free feature is demonstrated.Moreover

by studying the impacts of topology growth on error tolerance of the network

it is proved that enlarging the size of the local-world and enhancing the upper limit of de-gree is able to improve the network performance in terms of error-tolerance

while an increase in the cluster proportion and deletion probability led to the degradation of the network error tolerance.

关键词

Keywords

references

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